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Found 13 papers, 8 papers with code
A Template-guided Hybrid Pointer Network for Knowledge-based Task-oriented Dialogue Systems
Most existing neural network based task-oriented dialog systems follow encoder-decoder paradigm, where the decoder purely depends on the source texts to generate a sequence of words, usually suffering from instability and poor readability.
Ranked #9 on
Task-Oriented Dialogue Systems
on KVRET
Contextual Distillation Model for Diversified Recommendation
The diversity of recommendation is equally crucial as accuracy in improving user experience.
Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphs
Moreover, we extend our analysis of expressiveness and graph transformation to temporal graphs, exploring several temporal GNN architectures and providing an expressiveness hierarchy for them.
Working Memory Capacity of ChatGPT: An Empirical Study
Working memory is a critical aspect of both human intelligence and artificial intelligence, serving as a workspace for the temporary storage and manipulation of information.
Seminaive Materialisation in DatalogMTL
DatalogMTL is an extension of Datalog with metric temporal operators that has found applications in temporal ontology-based data access and query answering, as well as in stream reasoning.
An Empirical Study of Retrieval-enhanced Graph Neural Networks
Graph Neural Networks (GNNs) are effective tools for graph representation learning.
MeTeoR: Practical Reasoning in Datalog with Metric Temporal Operators
DatalogMTL is an extension of Datalog with operators from metric temporal logic which has received significant attention in recent years.
A Template-guided Hybrid Pointer Network for Knowledge-basedTask-oriented Dialogue Systems
Most existing neural network based task-oriented dialogue systems follow encoder-decoder paradigm, where the decoder purely depends on the source texts to generate a sequence of words, usually suffering from instability and poor readability.
Fast and Scalable Dialogue State Tracking with Explicit Modular Decomposition
We present a fast and scalable architecture called Explicit Modular Decomposition (EMD), in which we incorporate both classification-based and extraction-based methods and design four modules (for classification and sequence labelling) to jointly extract dialogue states.
Confusionset-guided Pointer Networks for Chinese Spelling Check
This paper proposes Confusionset-guided Pointer Networks for Chinese Spell Check (CSC) task.
A Hybrid Approach to Automatic Corpus Generation for Chinese Spelling Check
Chinese spelling check (CSC) is a challenging yet meaningful task, which not only serves as a preprocessing in many natural language processing(NLP) applications, but also facilitates reading and understanding of running texts in peoples{'} daily lives.
NLPTEA 2017 Shared Task -- Chinese Spelling Check
This paper provides an overview along with our findings of the Chinese Spelling Check shared task at NLPTEA 2017.
